robonet-ii robotic operations, system outline and data processing yiannis tsapras, 2008, lcogt,...
TRANSCRIPT
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RoboNet-II
Robotic operations, System outline and data processing
Yiannis Tsapras, 2008, LCOGT, Santa Barbara
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People
Y Tsapras (LCOGT) R Street (LCOGT) K Horne (St Andrews) (PI) C Snodgrass (ESO) D Bramich (ING) M Dominik (St Andrews) N Kains (St Andrews) N Rattenbury (Manchester) M Burgdorf (ARI)
A Allan (eSTAR/Exeter) E Hawkins (LCOGT) C Mottram (eSTAR/ARI) N Clay (eSTAR/ARI) I Steele (eSTAR/ARI) B Haworth (LCOGT) S Fraser (eSTAR/ARI)
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The telescope network
FTS+FTN+LT LCOGT
expansion plans (M. Falarski)
All telescopes used by microlensing teams
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System Layout
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The Robotic Control System
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The Robotic Control System
Runs on a computer at each telescope site Issues instructions to the software controlling the telescope
and instruments. It performs:• Start-up and end of night operations
• Observations (Science,ToO, RTI, background) Receives updates from local weather station and closes
down operations if parameters exceed allowed ranges Receives input from:
• Observer Support System (normal observations database)
• Target of Opportunity Control System (bypass normal operations)
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Requesting observations The Phase-II database contains all observation program details
[targets, configuration, exposures] All observations are part of proposals
• A proposal contains:• Groups of observations [specify:activation,expiration,monitoring,conditions]
• Individual observation requests [specify: instrument,position,repeats,exptime]
5 types of Groups:• Flexible -one off observations, can be performed any time
• Fixed -one off observations, performed at specific times
• Monitoring -periodic observations of same target, fixed interval
• Ephemeris -performed at given phase in a variable objects cycle
• MinInterval -performed at least the specified interval apart
microlensing
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Example of phase-II entry
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Example of phase-II entry
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Example of phase-II entry
Intelligent Agents create these entries automatically! (wait for a few more slides)
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Scheduling observations
When RCS requests next Group of observations…
All Groups in database are sorted by the Scheduling algorithm• In a rapidly changing environment, the
selected group is one that is best matched to current conditions
• Takes into account: local conditions, phase-II model, Group history. (Fraser S.,2006, AN, 327,779)
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Scheduling metrics Group scoring
• Slew time
• Lateness in project
• Time used in proposal relative to allocation
• Matching of actual condition to requested (seeing/lunar)
• Assigned priority level
• Proposal science priority
• Observing windows missed by monitor/ephemeris group Observation scoring
• Target location (height)
• Transit height fraction
• Distance from the moon
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What does this mean?
Observing programs in the database are constantly competing for telescope time
• We generally do not know when an observation will be performed or from which telescope (though we can have a pretty good guess)
• It was designed this way to accommodate a large global telescope network
• Only very basic user input, the system does the rest
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Intelligent agents
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Intelligent agents
eSTAR external agent• Receives prioritised list of targets regularly from
RoboNet-II (web-PLOP, every hour)
• Submits observation queries and requests to…
Telescope Embedded Agent (TEA & node agent)• Responds to eSTAR agent about telescope suitability
for specific observing request
• Handles the requests from external agents and updates Phase-II database
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Intelligent agents (addendum)
We can override normal observations manually via a webpage interface or from our iPod Touch while having coffee at Starbucks
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Prioritising the events
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Prioritising the events
Planet Lens Optimisation (“web-PLOP” Snodgrass 2008)
• Provides optimal target list for automated observing (updated every 15 min)
• Keeps up to date record of all data from OGLE,MOA,PLANET,RoboNet-II observations
• New fits performed when new data points arrive (PLENS,
SIGNALMEN, web page updates) List read by the eSTAR intelligent agent Receives input from anomaly detector (which tags anomalous
events as high priority) Prioritisation algorithm (Horne 2008, MNRAS, submitted)
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Anomaly detection
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Anomaly detection
Exploits the systems’ possibility of automated fast response and flexible scheduling (M. Dominik)
How?• Receives new data by rsync from RoboNet-II cluster (as soon
as these are processed by our pipeline)
• Data from other surveys also included
• Identifies new points that are deviating
• Action requests: check, anomaly, ordinary
• No manual intervention needed
• Currently this mode of override only works for real-time RoboNet-II data
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Quicklook Archiving
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Archives
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The reduction pipeline
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The reduction pipeline
Intercepts incoming microlensing data Performs an assessment of data quality Updates the log file of observations Moves data to the appropriate event directories If appropriate, identifies the target position on
reference (based on WCS fits to the finder charts) – R. Street
Initiates Difference Image Analysis pipeline
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The reduction pipeline
Creates a template reference frame Geometric and Photometric alignment of all images
to the reference frame Matches the seeing between each image and the
reference Subtracts each scaled image from the reference Variable stars leave a positive or negative residual Fits PSF to target Update photometry (also on web-PLOP, ARTEMiS and the
PLANET webpages)
OB08199
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The reduction pipeline (dfd)
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Results displayed “live”
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2008 e-mail exchanges (anomaly and high magnif.)
KB08075 KB08117-binary
KB08159-scatter at peak?
KB08171 KB08198 KB08199-binary
KB08267 KB08280 KB08308 KB08284-binary source
KB08310-planet?
KB08336 KB08380 KB08384-binary
OB08013 OB08208 OB08272 OB08210-peak anomaly
OB08270-planet?
OB08272 OB08320 OB08330 OB08342 OB08346 OB08349 OB08355 OB08378 OB08432 OB08493 OB08510-peak anomaly
OB08513-planet?
OB08559
32 emails alerting suspected anomalous behaviour OB08151
OB08209 OB08215 OB08290-finite source
OB08426 OB08509 KB08022 KB08096 KB08105 KB08225 KB08311 KB08383 KB08402 KB08415 KB08428-anomalous
KB08453
16 emails alerting possible high magnification
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KB08384
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OB08210
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OB08510
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KB08310
microFUN
•Probably a Saturn-like planet?, pretty close to the Einstein ring (preliminary model by Subo
Dong)•Strong Parallax signal
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OB08270
Preliminary modelling based on microFUN + SAAO data around the peak seem indicate the presence of Jovian planetary companion
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OB08513
q~0.018?
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OB08513
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2008 season summary Time used : 313.16 hours Events observed: 502, 266(>5 data points)
Data FTN FTS LT
• Used : 1602 5494 1294
• Rejected: 363 2375 1118(?)
• Total : 12246 [used:8390/rejected:3856]
Events observed: 331, 214(>5 data points)
Data FTN FTS LT• Used : 1016 5965 611
• Rejected: 182 5921 318
• Total : 14013 [used:7592/rejected:6421]
2007
>5 dp : 204.04 hrs (65%) <5 dp : 10.37 hrs (3%) Rejected : 98.75 hrs (32%)
What fraction of the time?
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Issues Software: deploy, debug, maintain…
• Introduce extra internal monitoring, auto-recovery mechanisms where possible
School programs (1 to 4 hours on most nights)• Not much we can do. Wait for 0.4m deployment
FTS performance (main microlensing telescope)• Still room for improvement, engineering trip planned
Data display problems• Target misidentification by the pipeline, incorrect lightcurves
(you may have noticed the huge error bars on some RoboNet-II data on ARTEMiS plots)
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“wouldn’t it be nice…”
Agree on a common data format • so that teams can exchange data efficiently
Associate data points on graphs with statistics on images • Information readily accessible
Fit binary events automatically• with preliminary models displayed “live”
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Websites
http://robonet.lcogt.net/ (RoboNet-II homepage)
http://lcogt.net/ (LCOGT website)
http://microlensing.lcogt.net/ (microlensing discussion forum)
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Fin
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Other event examples
KB08284
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FTS image quality
2007 problems: bipolar images, bad tracking…
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FTS image quality
2008 (on a good night)